Water leak detection device and integration platform

ABSTRACT

A water monitoring system has aback-end system comprising an authentication module, a machine learning module, an alerts module, and a third-party module. The back-end system remotely connects to a local system which has a water monitoring device and the authentication module authenticates the connection relative to a user. The back-end system remotely connects to a third-party system using the third-party module and the authentication module authenticates the connection relative to the same user. The back-end system receives data from the local system and the third-party system, the machine learning module analyzes the data to determine one or more rules which identify water usage as intended or unintended, and the alerts module provides an alert to one or more of the local system, the third-party system, or a client device when the water monitoring device measures water flow data which indicates a leak according to the one or more rules.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.No. 62/695,548 filed Jul. 9, 2018, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

The present disclosure relates generally to a water leak detectiondevice, and, more particularly, to an overall water meter integrationplatform utilizing the water leak detection device and other connecteddevices.

BACKGROUND

Plumbing systems are a critical aspect of all modern buildings andintroduce significant risk due to the nature of inserting a pressurizedwater supply throughout a structure. Plumbing leaks, from small drips toburst pipes, can cause significant damage to any building. Burst pipesand water damage present significant costs for repairs and increasedwater and sewer bills for homeowners and property managers. Further,billions of dollars are paid by insurers in water damage claims everyyear. A significant portion of these costs could have been avoided ifwater leaks were identified quickly and remediation steps implementedsoon thereafter. In addition, leaks, even small drips, waste asignificant amount of water, thereby raising water costs and reducingvaluable resources.

Presently, much of the problems associated with water leaks stem fromthe relative inaccessibility of plumbing systems in both residential andcommercial settings. For example, a leak may be behind a wall or in acabinet which is not readily apparent. Further, even when leaks arefound or major flooding events occur, the procedure for addressing theproblem and turning off the water supply may be an unfamiliar process,which may delay remedial actions and enhance damage and costs. In mostsituations, a water meter and main valve is located at a main waterentry point. The water meter tracks usage information for the home orcommercial space. The main valve, when closed, ceases the flow of waterto the downstream plumbing and in many cases is the only immediateoption for stopping a leak or burst pipe flow. The main valve is usuallylocated in a remote location (a basement or utility room) which may ormay not be anywhere near the leak or anyone capable of finding the valveand turning off the water.

Currently, there are systems which are configured to automatically shutoff the water at the main valve under certain conditions. For example,some systems are configured to turn off the main valve when the waterflow continues through the water meter for an extended period of time.Other systems rely on an array of sensors and valves spread throughoutthe building in order to detect various circumstances which cause themain valve to be closed. However, these automatic shutoff systems andother current devices are not ideal and suffer from drawbacks.

In particular, systems which monitor the water meter and shut off thevalve only when significant deviations from normal flow occur do notaddress most leak situations and likely will shut off the water wellafter much of the damage has already occurred. Systems which utilize asuite of sensors throughout a building are complicated and expensive andoften rely on specific input from a user to understand when conditionsare normal and when a leak is occurring.

The present disclosure is directed to overcoming these and otherproblems of the prior art.

SUMMARY

In some embodiments, a computer-implemented method for detecting a leakin a water flow system is disclosed. The method includes connecting to awater monitoring device and a third-party system, receiving water flowdata from the water monitoring device, receiving location data from thethird-party system, determining a threshold parameter based on thelocation data, and comparing the water flow data to the thresholdparameter in order to determine that there is a leak in the water flowsystem.

In other embodiments, a water monitoring system is disclosed. The watermonitoring system includes a back-end system comprising anauthentication module, a machine learning module, an alerts module, anda third-party module. The back-end system is configured to remotelyconnect to a local system comprising a water monitoring device and theauthentication module is configured to authenticate the connectionrelated to a user. The back-end system is configured to remotely connectto a third-party system using the third-party module and theauthentication module is configured to authenticate the connectionrelated to the same user. The back-end system receives data from thelocal system and the third-party system, the machine learning module isconfigured to analyze the data to determine one or more rules whichidentify water usage as intended or unintended, and the alerts module isconfigured to provide an alert instruction to one or more of the localsystem, the third-party system, or a client device when the watermonitoring device measures water flow data which indicate a leakaccording to the one or more rules.

Additional features and advantages of the invention will be madeapparent from the following detailed description of illustrativeembodiments that proceeds with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other aspects of the present invention are bestunderstood from the following detailed description when read inconnection with the accompanying drawings. For the purpose ofillustrating the invention, there are shown in the drawings embodimentsthat are presently preferred, it being understood, however, that theinvention is not limited to the specific instrumentalities disclosed.Included in the drawings are the following Figures:

FIG. 1 is a schematic diagram of an exemplary water monitoring system,consistent with disclosed embodiments;

FIG. 2 is a schematic diagram of an exemplary back-end system of thewater monitoring system of FIG. 1, consistent with disclosedembodiments;

FIG. 3 is a schematic diagram of an exemplary local system of the watermonitoring system of FIG. 1, consistent with disclosed embodiments;

FIG. 4 is a schematic diagram of an exemplary water monitoring device ofthe local system of FIG. 3, consistent with disclosed embodiments;

FIG. 5 is an exploded view of an exemplary water monitoring device,consistent with disclosed embodiments;

FIG. 6 is a flowchart of an exemplary learning process, consistent withdisclosed embodiments;

FIG. 7 is a flowchart of an exemplary learning process using third-partysystem integration, consistent with disclosed embodiments;

FIG. 8 is a flowchart of an exemplary alerting process, consistent withdisclosed embodiments;

FIG. 9 is a flowchart of an exemplary alerting process using third-partysystem integration, consistent with disclosed embodiments;

FIG. 10 is an exemplary user interface which may be presented using adisplay, consistent with disclosed embodiments;

FIG. 11 is another exemplary user interface which may be presented usinga display, consistent with disclosed embodiments;

FIG. 12 is another exemplary user interface using a display, consistentwith disclosed embodiments; and

FIG. 13 is another exemplary user interface which may be presented usinga display, consistent with disclosed embodiments.

DETAILED DESCRIPTION

The present disclosure describes a water leak detection device and anintegration platform which allows the detection device to be compatiblewith other devices and incorporates collected data from all deviceswithin the system, including third-party devices, in order to provide acomprehensive system which fits within an overall building automationscheme. The water leak detection device includes monitoring componentswhich are configured to collect data related to a flow of water into orthrough a building, such as a residence or commercial structure, andcomputing components which are configured to establish rules fordetermining when a leak or other unintended water event occurs withinthe plumbing system. The integration platform provides a centralizeddata location for receiving collected data from a user's water leakdetection device, other user's water leak detection devices, user clientdevices, and third-party devices and systems, thereby enabling the waterleak detection device to easily integrate into a user's daily life byproviding multiple communication options for learning from and alertingthe user. The integration platform further enhances the data set whichis available to the water leak detection device for setting rules whichcan be implemented to accurately identify leaks and other unwanted waterflows and perform corrective actions accordingly.

The water leak detection device is connected to a back-end system whichincludes a specialized configuration which incorporates machine learningto determine the customized rules for the detection device to use indetermining when a leak event occurs. The back-end system collects datafrom multiple different devices and sources and uses artificialintelligence in order to learn behavior patterns of the users andimprove the algorithms that make decisions on system modes andcorrective actions.

The water leak detection device incorporates an intuitive control systemwhich is convenient to the user. The control panel is configured forproviding information to the user and receiving input data. The controlpanel provides a connection point to the user which is conventionallynot present in water meter systems and allows for customizedinput/output. The control panel eases manual control over the system,providing access to control one or more valves or water flow restrictionmechanisms within the plumbing system. The control system furtherincludes network compatibility which allows the control panel to bepresented on one more client devices, such as personal computers ormobile devices such as smart phones and tablets. The back-end system mayinclude features which provide a mobile application to the user's mobiledevice, thereby serving as the connection point and allowing the user toprovide control input and receive information such as statistics andalerts. The integration with third-party systems provides yet anotherchannel for communication with the user.

The water leak detection device and integration platform provide anefficient and integrated approach to alerting a user of a leaksituation. For example, the integration platform at the local andback-end locations and connections to third-party systems providesseveral options for performing an action which ultimately helps totemper any damage caused by the leak. In one example, the integrationwith third-party systems allows an alert to be transmitted in a mannerwhich maximizes the possibility that it will be viewed by the user.Examples include a message pushed to a smart phone, an audible alertplayed through a security system or smart speaker, or a phone call froman operator. Further, the integration of third-party systems allows foradditional data, such as location data, to be considered whendetermining how to contact the user. For instance, if the user is athome, an alarm may sound, and if the user is away, a call or textmessage may be sent. These features can carry into other correctiveactions, including shutting off the water, which is an action that maybe automatically carried out in certain situations.

While the embodiments described herein are discussed in relationship toa plumbing system (also referred to herein as a water flow system), itshould be understood that the disclosed systems, devices, and componentsare not limited to being used with water flow systems. The disclosedembodiments may be applicable to other fluid systems, such as naturalgas systems, cooling systems, lubrication systems, vehicles, etc.

FIG. 1 is a schematic diagram of a water monitoring system 100. In anexemplary embodiment, the water monitoring system 100 includes aback-end system 110, a local system 120, a client device 130, athird-party system 140, and a network 150. As shown, the back-end system110 may be a central computing system configured to connect to the localsystem 120, client device 130, and third-party system 140 eitherdirectly or through the network 150. The network 150 is shown as asingle network but can be multiple different networks facilitatingconnections between components of the water monitoring system 100. Forexample, the back-end system 110 and local system 120 may be directlyconnected.

The back-end system 110 is a computing device which is configured toperform one or more monitoring functions through processing and datacommunication with the other components of the system 100. The back-endsystem 110 may be a server that includes components, includingprocessors, memory, databases, etc., which enable analysis, alerts, andaction based on data received from the local system 120 (or othercomponent of system 100) and through the transmission of data to thelocal system 120 (or other component of the system 100).

The local system 120 is associated with a building or structure 160which includes a water flow system 170. The water flow system 170 may bea network of pipes which deliver water to fixtures located throughoutthe interior and/or exterior of the building 160. These include kitchenfixtures, bathroom fixtures, outdoor faucets, sprinkler systems, etc.The building 160 may be a residential or commercial building. Thebuilding 160 may represent a portion of an overall building, such as atownhome, apartment, or office space. The local system 120 is connectedto the water flow system 170, such as at a main water inlet 180.

The local system 120 is a computing device which is configured toperform one or more monitoring functions through processing and datacommunication with the other components of the system 100. The localsystem 120 may include a personal computing device, such as a laptop ordesktop computer, or may be built into a separate device. The localsystem 120 preferably includes one or more processors and memory deviceswhich enable the monitoring processes described herein.

The local system 120 is configured to collect water flow data from thewater flow system 170, such as flow rate, temperature, pressure, etc.The local system 120 is configured to provide the water flow data to theback-end system 110. The local system 120 is also configured to performactions based on the water flow data and other inputs. For example, thelocal system 120 may be configured to provide information to a controlpanel or the client device 130 to inform a user P. While the localsystem 120 is shown associated with a single building 160 and user P, itshould be understood that a plurality of local systems associated withother buildings 190 may also be connected as part of the watermonitoring system 100. These additional local system provide additionaldata to the back-end system 110 which can be used in generating rulesand features which are provided to the local system 120. In other words,the back-end system 110 is configured to learn from the data and improvethe connected systems over time.

The client device 130 is a computing device which is connected to thenetwork 150 for communication with other devices in the water monitoringsystem 100. The client device 130 may be, for example, a mobile devicesuch as a smart phone or tablet. In other embodiments, the client device130 may be a smart speaker, such as those provided by Amazon, Apple, orGoogle. In other embodiments, the client device 130 may be a laptop ordesktop computer. In one aspect, the client device 130 is configured asa terminal to present information to the user P. For example, the clientdevice 130 includes a screen which can provide information, such asmeasurements, usage statistics, and alerts, to the user P. In anotheraspect, the client device 130 is configured to collect data as inputfrom the user P. This data may include input such as settings orresponses to questions regarding water usage. In another aspect, thedata may include data which is normally collected through third-partyfunctions of the client device 130. For example, the client device 130may collect location data which is associated with the user P. Inanother example, the client device 130 may collect voice data based oncaptured speech of the user P.

The third-party system 140 is an additional computing device which isinterconnected within the water monitoring system 100. For example, thethird-party system 140 may be associated with a third-party entity, suchas an entity which provides a service to the user P and which collectsdata. In one embodiment, the third-party system 140 is associated with avirtual assistant service, such as Alexa® (Amazon), Siri® (Apple),Google Assistant®, or the like. The third-party system 140 may include aserver or other computing device which receives data from a clientdevice, such as the client device 130.

One or more of the back-end system 110, local system 120, andthird-party system 140 may include a mobile application which isprovided to the user P through the client device 130. The client device130, through the mobile application(s) provides an interface for theuser P to control one or more aspects of the components of the watermonitoring system 100. The back-end system 110 preferably furtherincludes a configuration which enables and eases integration ofthird-party services into the overall water monitoring system 100. Forexample, the back-end system 110 may be configured with an open APIwhich enables integration of third-party components and services withinthe same network 150. In this way, the back-end system 110 is configuredto augment the water monitoring services provided through the localsystem 120 with data and services which are associated with thethird-party system 140.

The network 150 includes one or more network connections which enabledata transfer between one or more components of the water monitoringsystem 100. For example, the network 150 may be the Internet, with eachsystem within the water monitoring system 100 including an Internetconnection device. The network 150 may also include one or moreconnections through Wi-Fi or Bluetooth™ which enable data transferbetween components. In some embodiments, the network 150 may include oneor more cloud-computing services, such as data storage and transfer.

FIG. 2 is a schematic diagram of an exemplary embodiment of the back-endsystem 110. The back-end system 110 includes a processor 210, memory220, one or more I/O devices 230, one or more control modules 240-270,and a data storage device 280. The processor 210 and memory 220 may bespecifically configured to implement the disclosed processes. The I/Odevice 230 may include, for example, communication components whichenable the back-end system 110 to send and receive data to and fromother components of the water monitoring system 100.

The control modules 240-270 may include, for example, an authenticationmodule 240, a machine learning module 250, an alerts module 260, and athird-party module 270. The control modules 240-270 may be implementedin hardware or software. For example, the control modules 240-270 mayinclude software instructions which are stored in the memory 220 or intheir own hardware component and which are executed by the processor 210in order to carry out an associated process. The control modules 240-270are exemplary and other control modules may be used in addition to or inplace of the control modules described herein. Moreover, while thecontrol modules 240-270 are depicted as separate components of theback-end system 110, it should be understood that the control modulesmay be interconnected, combined, or located elsewhere within the watermonitoring system 100.

The authentication module 240 is configured to monitor and authenticatedata communications between the back-end system 110 and other deviceswithin the water monitoring system 100. For example, the authenticationmodule 240 is configured to provide an access token for each sessionbetween back-end system 110 and local system 120, back-end system 110and client device 130, and back-end system 110 and third-party system140. The back-end system 110 stores information about the user P,including information which identifies the local system 120, clientdevice 130, and any third-party accounts associated with the user P. Theauthentication module 240 is configured to store and recall a uniquetoken to distinguish each device upon communication with the back-endsystem 110, thereby associating multiple devices with a single user Pand enabling the back-end system 110 to distinguish between them.

The machine learning module 250 is configured to analyze data receivedfrom the network 150 and identify patterns and generate rules which helpto define behavior of the user P and the logic which will be used withinthe water monitoring system 100 for alerting the user P. For example,the machine learning module 250 may receive water usage statisticsincluding amount of water usage and timing of water usage to determinepatterns which define the normal usage of water by the user P at thebuilding 160. The machine learning module 250 may also consider dataacross multiple local systems associated with the plurality of buildings190. The machine learning module 250 is configured to use the usage datato determine rules for when water usage is likely to be planned and whenit is indicative of a leak (e.g., pipe burst). The machine learningmodule 250 may also be configured to determine rules for different waterusage modes. For example, the machine learning module 250 may determinewhen the local system 120 should be placed in a “home” or “away” mode.These modes may include different usage expectations, further refiningthe capability of the back-end system 110 to determine between genuinewater usage and leaks.

The alerts module 260 is configured to provide a message or alert to oneor more devices within the water monitoring system 100. For example, thealerts module 260 may receive an indication that a major leak isoccurring at the building 160 and route a message to the user P throughthe local system 120, the client device 130, and/or the third-partysystem 140. The alerts module 260 is also configured to receiveinformation back from local system 120, the client device 130, and/orthe third-party system 140 which can be used to stop the alert. Forexample, the user P may provide input to the client device 130 which isdelivered to the alerts module 260. The input may indicate that the userP is not home and a corrective action, such as turning off the water,should be taken. The alerts can be customized and may depend on thesituation. For example, the machine learning module 250 may cause thealerts module 260 to send different messages depending on the type ofleak identified and the home/away status of the user P.

In an exemplary embodiment, the alerts module 260 is configured todetermine an alert instruction depending on the leak situation. Thealert instruction may include sending an alert to the user P through theclient device P. In another example, the alert instruction may includeperforming a corrective action, such as by automatically shutting offthe water through the local system 120.

The third-party module 270 is configured to facilitate communicationbetween the back-end system 110 and the third-party system 140. In oneembodiment, the third-party module 270 is an open API device whichallows various third-party systems 140 to integrate with the back-endsystem 110. The third-party module 270 is at least partly responsiblefor integrating the local system 120 into an overall home automationscheme which accomplishes several objectives. First, the integration ofthird-party systems 140 provides additional access to data which isrelevant to the water monitoring system 100. Second, the third-partymodule 270 allows the user P to interact with the back-end system 110through existing automation tools, such as a smart speaker. In this way,the local system 120 and/or an associated device, becomes an additionalautomation tool or an Internet of Things device which is part of an opensystem.

FIG. 3 is a schematic diagram of an exemplary embodiment of the localsystem 120. The local system 120 may include a water monitoring device310 which has a local integration platform 315. The local integrationplatform includes at least a processor 320, a memory 330, and I/Odevices 340. The water monitoring device 310 further includes one ormore internal sensors 350 and one or more internal valves 360. The localsystem 120 may also include one or more external sensors 370 and one ormore external valves 380. It should be understood that the depiction ofthe local system 120 is exemplary and that other arrangements arepossible, including various connections between the components,integration of the components, or movement of the components elsewherewithin the water monitoring system 100.

The water monitoring device 310 is installed in the building 160 tomonitor the water flow system 170 at the main water inlet 180. Theintegration platform 315 includes computing components which areconfigured to connect the local system 120 to the network 150 andprovide collected data to the back-end system 110 and connects the watermonitoring device 310 to the other components of the water monitoringsystem 100. The integration platform 315 thereby integrates the watermonitoring device 310 into an overall automation scheme and thus can beviewed as an Internet of Things device which serves as a watermonitoring data source. The processor 320 is configured to executeinstructions stored in the memory 330 in order to perform one or moreassociated processes, such as determine when and what data to send tothe back-end system 110. The I/O devices 340 include an interface suchas a touch screen which presents information to the user P. The I/Odevices 340 also include data connection elements which facilitate datacommunication with the other components of the water monitoring system100.

The internal sensors 350 and internal valves 360 are mechanicalcomponents of the water monitoring device 310. The internal sensors 350may include, for example, flow rate, temperature, and pressure sensorswhich are configured to measure associated parameters at the main waterinlet 180. The internal valves 360 include one or more valves which areconfigured to control flow through the water flow system 170 at the mainwater inlet 180. The internal valves 360 may include, for example, anautomatic shut-off valve which is controlled by the water monitoringdevice 310 to cease the flow of water. The internal valves 360 may alsoinclude a manual shut-off valve which allows the user P to stop thewater flow.

The external sensors 370 and external valves 380 are mechanicalcomponents of the local system 120 which may be located remote from thewater monitoring device. The external sensors 370 could include one ormore pressure, temperature, moisture sensors, or proximity sensors whichare configured to detect a parameter somewhere in the building 160 otherthan at the main water inlet 180. For example, a moisture sensor may beplaced at a potential leak spot such that the water monitoring device310 can be configured to detect a leak based on a reading from one ofthe external sensors 370. The external valves 380 may include one ormore remote valves located somewhere in the water flow system 170 otherthan the main water inlet 180. The external valves 380 may be remotelycontrollable by the local integration platform 315 to turn off only aportion of the water flow in the water flow system 170. For example, aleak may be detected by an external sensor 370 in a particular room ofthe building 160 and the water monitoring device 310 may close anexternal valve 380 associated with that particular room such that thewater flow is stopped to the location of the leak, but the entire waterflow system 170 is not shut off.

In embodiments in which the local system 120 is associated with acommercial building, such as an apartment or office building, the localsystem may include a plurality of water monitoring devices 310, each ata separate location (e.g., to monitor separate apartments or offices). Acentral integration platform 315 may be connected to each of the watermonitoring devices 310 and may collect data from each and transmit thedata to the back-end system 110. The integration platform 315 mayinclude an authentication module which is configured to identify theparticular water monitoring device 310 and store a token whichassociates a user P with the correct water monitoring device 310.

FIG. 4 is a schematic diagram of an exemplary embodiment of the watermonitoring device 310. The water monitoring device 310 includes anexemplary embodiment of the local integration platform 315 and a suiteof valve and board sensors 410. The valve and board sensors 410 areconnected in relation to a pipe 420 which makes up a portion of thewater flow system 170 at the main water inlet 180. The valve and boardsensors 410 preferably include a small leak sensor 430, a temperaturesensor 440, and a water flow sensor 450. The small leak sensor 430 ispreferably a pressure sensor configured to measure a pressure in thepipe 420. The small leak sensor 430 is configured to monitor pressurevalues and provide the data to the local integration platform 315 forbeing provided to the back-end system 110 and/or for determining thepresence of a leak within the water flow system 170. In anotherembodiment, the small leak sensor 440 may be a vibration sensor. Thevibration sensor may be configured to monitor the water flow system 170for vibrations which may indicate the presence of a leak. Thetemperature sensor 440 and water flow sensor 450 are configured tomeasure associated data (e.g., temperature, flow rate) and provide thedata to the local integration platform 315 and, in some cases, theback-end system 110. The local integration platform 315 is configured toconstantly update certain parameters of water flow based on readingsfrom the sensors 430-450.

The water monitoring device 310 also includes a valve power supply 460and at least one valve 470. The powered valve 470 is configured to ceaseflow by closing a portion of the pipe 420 at the location of the valve,based on a signal from the power supply 460. The valve 470 may be, forexample, a ball valve which is controlled based on an electric signal.The valve and board sensors 410 further include a controller 480 andmemory 490 which are configured to provide signals to close and/or openthe valve 460 based on communication with the local integration platform315.

FIG. 5 is an exploded view of an exemplary embodiment of the watermonitoring device 310. The water monitoring device 310 includes ahousing 510 for enclosing the local integration platform 315 and thevalve and board sensors 410. The local integration platform 315 includescomputing components including processors and memory 520, a power source530, and a control panel 540. In one embodiment, the power source 530may include a power cord for connecting a building power supply (notshown) and/or a back-up battery that may provide power when the primarypower source is not available (e.g., during a power outage). The housing510 includes a window 545 for receiving the control panel 540 andallowing a user P to view and interact with the control panel 540.

In the illustrated exemplary embodiment, the valve and board sensors 410include flow sensor 550, pressure sensor 552, and temperature sensor554. Additional components may include, for example, a real time clock556 and a siren/alarm 558. The valve and board sensors 410 also includevalves for controlling the flow of water through the water monitoringdevice 310. The valves include, for example, an automatic shut-off valve560 and a manual shut-off valve 570.

The water monitoring device 310 further includes a connection element580. The connection element 580 includes a pipe section which isconfigured to be installed into the water flow system 170. Theconnection element 580 includes an inlet section and an outlet sectionwhich are inserted into the water flow system 170 downstream of the mainwater inlet 180 such that water flows into the inlet section from themain water inlet 180 and out of the outlet section to the rest of thebuilding 160. The valve and board sensors 410 are located in and aroundthe connection element 580 in a manner to collect relevant data, such astemperature, pressure, flow rate, vibration, etc (e.g., via sensors 550,552, and 554). The automatic shut-off valve 560 includes a powered valvewhich is controlled by the local integration platform 315 to open andclose at selected times. The housing 510 preferably includes a handle590 which is connected to the manual shut-off valve 570 which allows theuser P to manually turn off the water at the location of the watermonitoring device 310.

FIG. 6 is a flowchart of an exemplary learning process 600 for trainingthe back-end system 110 for alerting the user P and controlling theautomatic shut-off valve 560 via the water monitoring device 310. Theback-end system 110 performs one or more steps of the learning process600, such as by the processor 210 executing instructions stored in thememory 220. In some embodiments, the modules 240-270 or one or moreother modules may include software or hardware which is incorporatedinto the learning process 600.

In step 610, the back-end system 110 collects data. The local system 120receives data and transmits the data to the back-end system 110. In oneexample, this data includes water monitoring data from the watermonitoring device 310. The water monitoring data includes, for example,water flow statistics gathered by the sensors 430, 440, and 450. In anembodiment, the back-end system 110 receives a water usage map whichincludes detailed water use and the associated time of the use,including time, date, day of the week, etc. The back-end system 110 mayalso collect location data associated with the user P, such as locationdata collected by the local system 120.

In step 620, the back-end system 110 receives input setting data. Thelocal system 120 may receive input setting data as input from the user Pand provide the data to the back-end system 110. The input setting dataincludes information which further provides indicators of normal waterusage within the building 160. For example, the input setting data mayinclude a normal work schedule of the user P such that the back-endsystem 110 is apprised of when to expect the user P to be home. Inanother example, the input setting data includes a schedule for normalwater use, such as the timing of an irrigation system (e.g., sprinklersystem). In another example, the input setting data may include customwater leak thresholds. For example, the user P may input thresholdswhich represent unintended use of water within the building 160. In someembodiments, the thresholds may include a “home” mode threshold and an“away” mode threshold.

In step 630, the back-end system 110 requests and receives additionalinformation. The additional information may include further informationabout normal water usage. For example, the back-end system 110 mayidentify a water usage event and request additional information, such aswhether the water usage event is a normally scheduled occurrence orwhether it was a one-off event. The back-end system 110 may provide therequest for additional information to the local system 120 and/ordirectly to the client device 130 such that the user P can provide therequested information.

In step 640, the back-end system 110 analyzes the information receivedin steps 610-630 and determines and/or updates rules associated withnormal water usage. For example, the back-end system 110 may identifycertain water flow thresholds which would fall outside of normal wateruse for the particular building 160. These thresholds may vary dependingon the time of day, day of the week, month, etc. The thresholds mayadditionally or alternatively depend on the location of the user P. Forexample, if the user P is not at the building 160, the threshold fornormal water use may be lower than when the user P is present.

The learning process 600 may take place after an initial installation ofa water monitoring device 310 to thereby allow the back-end system 110to learn about the habits of the user P (and any other associatedusers). The machine learning module 250 may include one or more softwareprocesses which are carried out to generate information requests (step630) and water value thresholds (step 640) which are used as rules fordetermining when a water usage is intended and when it represents anunwanted use, such as a burst pipe. These rules set parameters for whenthe back-end system 110 and/or local system 120 should provide an alertto the user P and/or should take a corrective action such as shuttingoff the water by way of the water monitoring device 310. The learningprocess 600 may continuously repeat by gathering information from thevarious components in the water monitoring system 100 (steps 610-630)and updating the rules based on the collected data and machine learningalgorithms (step 640).

FIG. 7 is a flowchart of another exemplary process 700 for the back-endsystem 110 to perform machine learning to further establish rules forthe water monitoring device 310. The back-end system 110 may perform oneor more steps of process 700 in order to further refine the rules whichdefine actions which are taken by the back-end system 110 and the localsystem 120. In some aspects, the process 700 is part of the integrationplatform of the water monitoring system 100 in that the process 700includes steps for allowing the third-party system 130 to provideinformation which is used by the back-end system 110 to control thewater monitoring device 310.

In step 710, the back-end system 110 connects to the third-party system140. This may include the back-end system 110 registering an accountwith the third-party system 140 and performing an authentication withthe authentication module 240 in order to associate the third-partyaccount of the user P with their back-end system account. Thethird-party system 140 may be associated with an automation service,such as those provided by Amazon, Apple, Google, etc. The third-partysystem 140 may register with the back-end system through the third-partymodule 270 (e.g., via an open API) in order to integrate third-partyservices into the back-end system 110.

In step 720, the back-end system 110 receives data from the third-partysystem 140. For example, the back-end system 110 may receive locationdata from a third-party system 140 with access to location data. In oneexample, the third-party system 140 is associated with a security systemwhich monitors a status of the building 160. The security system maytrack location data which includes whether the user P is at the building160 or away (i.e., depending on an armed/unarmed status of the securitysystem). In another example, the third-party system 140 may beassociated with a location-based service, a feature which has becomecommon with many mobile applications. The third-party system 140 mayreceive location data associated with the user P based on the locationof the client device 130 which is running the associated application. Inyet another example, the third-party system 140 is associated with asmart speaker which includes a microphone and is configured to listenfor speech within the home to determine whether the user P (or anotherindividual) is present. The location data can also be mapped accordingto the time, date, and day of the week, indicating when the user P ishome and when the user is away.

In step 730, the back-end system 110 updates the rules associated with alocal system 120 based on information received from the third-partysystem 140. For example, the back-end system 110 (e.g., through themachine learning module 250) may modify an expected schedule of when theuser is home or away and may match the location data to water usage.This information further provides the back-end system 110 with datawhich shows patterns of usage of water within an associated building160. For example, the back-end system 110 may determine that water usagenever exceeds a certain threshold when the user is away from thebuilding 160 and set the threshold for an “away” mode accordingly.

In step 740, the back-end system 110 is configured to set a status forthe water monitoring device 310. For example, the machine learningmodule 250 may review location information to determine whether thewater monitoring device 310 should enter a “home” mode or an “away”mode. Each mode may include different rules or thresholds which indicatea particular action that should be taken. For example, when the watermonitoring device 310 is in a “home” mode, the thresholds for normalwater use are much higher than the thresholds associated with the “away”mode.

In step 750, the back-end system 110 provides the update rules andstatus to the water monitoring device 310. The water monitoring device310 is thereby continuously updated with rules and a current home/awaystatus through machine learning which accounts for information which isnot directly determined by the water monitoring device 310. Inparticular, data collected through third-party systems 140 supplementsthe data and rules from the learning process 600 in order to provide amore comprehensive artificial intelligence scheme which more accuratelyassesses and identifies water usage.

FIG. 8 is a flowchart of an exemplary alert process 800, consistent withdisclosed embodiments. In some embodiments, the local system 120 mayperform one or more steps of the process 800 in order to provide analert to a user. The process 800 may be performed based on rules orcontrol logic which is stored by the local integration platform 315 andwhich are received from the back-end system 110. In other embodiments,the back-end system 110 may perform one or steps of the process 800,such as in situations in which the rules or control logic is stored bythe back-end system 110.

In step 810, the water monitoring device 310 collects water flow datathrough the sensors (e.g., sensors 430, 440, 450). The water flow dataincludes one or more of flow rate, temperature, pressure, and vibrationmeasurements which are taken periodically over time. The watermonitoring device 310 collects the data and, in step 820 provides thedata to the back-end system 110 through the local integration platform315. The back-end system 110 receives the data, updates rules throughthe machine learning processes (e.g., process 600), and provides theupdated rules back to the water monitoring device 310.

In step 830, the water monitoring device 310 further performs a checkaccording to the current rules or control logic in order to detect aleak. For example, the water monitoring device 310 may compare apressure or flow rate measurement to a threshold to determine whetherthe water usage is likely unintended and thus a leak is occurring. Thethreshold may be based on the rules and therefore may depend on factorssuch as day of the week, date, time, home/away status, in order toaccurately represent water usage as expected or unexpected.

In another example, the water monitoring device 310 may identify a leak,such as a small leak, based on a stored pattern associated with such aleak. For example, a very small flow rate over a long period of time maybe associated with a small leak. In another example, the watermonitoring device 310 may be configured to identify vibration patternswithin the water flow system 170 to identify a leak.

In step 840, the water monitoring device 310 initiates an alert tonotify the user P. For example, the water monitoring device 310 mayidentify an leak and cause an alert instruction to be sent to the clientdevice 130, thereby alerting the user P of the situation. The alertinstruction may depend on the leak which is identified (e.g., based onthe severity of the situation). For a large leak (e.g., burst pipe), thewater monitoring device 310 may send a push notification (e.g., througha mobile application) which notifies the user P immediately. Otheroptions for alerting the user P include text message, email, phone call,etc. For a small leak, the water monitoring device 310 may only presenta notification locally on an interface, such as the control panel 540.In another embodiment, the water monitoring device 310 may sound analarm as an audible alert.

While the water monitoring device 310 is described as alerting the userP, it should be understood that any of the components of the watermonitoring system 100 may cause the alert to be provided to the user P(e.g., through the client device 130). For example, the back-end system110 may identify the leak based on the data received in step 830. Theback-end system 110 may additionally or alternatively perform a leakdetection analysis (e.g., step 830) to identify abnormal water usage andprovide an alert to the client device 130.

The integration platform 315 or back-end system 110 may generate thealert instruction based on a status mode of the water monitoring device310. For example, if the water monitoring device 310 is in an “away”mode, the alert instruction may be delivered to a client device 130which is likely to be with the user P, such as a smart phone. Inaddition, the alert instruction may be delivered to a third-party system140, such as a third-party which may be capable of contacting the user Pand/or dispatching a remediation team to the building 160. If the watermonitoring device 310 is in a “home” mode, the alert instruction mayinclude a message to a client device 130 which is likely to be in rangeof the user P, such as a smart speaker or security system.

In step 850, the water monitoring device 310 performs a correctiveaction in certain situations. For example, when a major leak is detected(e.g., burst pipe, leak for a long period of time), the water monitoringdevice 310 may determine that the water should be shut-off to minimizewater damage from the potential leak. The water monitoring device 310may use the stored rules or control logic to determine which leaksidentified in step 840 are associated with a corrective action andperform the corrective action when needed. For example, the watermonitoring device 310 may send a signal to close the automatic shut-offvalve 560.

While the corrective action may be automatic based on the control logic,in other embodiments or instances the corrective action may be performedbased on input from the user P. For example, after receiving anotification that a leak is occurring, the user P may enter aninstruction to turn off the water. This may include the client device130 receiving the input instruction and transmitting the instruction tothe water monitoring device 310, either directly or through one or moreof the back-end system 110 and third-party system 140. In anotherexample, the user P may provide input directly to the water monitoringdevice 130, such as through the control panel 540.

The water integration platform 315 and/or the back-end system 110 isalso configured to determine whether to perform a corrective actionbased on the alert instruction from step 840. For example, some alertinstructions may include an associated corrective action, such as anautomatic water shut-off. In this way, the corrective action may dependon certain conditions, such as the “home” or “away” status of the watermonitoring device 130.

FIG. 9 is a flowchart of an exemplary process 900 for providing an alertto the user through an integrated third-party system 140. The process900 may be used in addition to or alternative to the process 800 and maybe a specific embodiment of the process 800. The water monitoring device310 (e.g., through the local integration platform 315) may perform oneor more steps of the process 900 to communicate with the user P througha client device 130 associated with a third-party system 140.

In step 910, the water monitoring device 310 identifies abnormal waterusage. For example, the water monitoring device 310 may compare waterflow data to stored rules or control logic to determine whether a leakis occurring. The water monitoring device 310 may identify a leakthrough one or more of the leak detection processes described herein.For example, the small leak sensor 430 may detect a water pressure orvibration pattern which indicates a leak has occurred.

In some embodiments, the water monitoring device 310 may be connected toa third-party system 140 capable of detecting a leak or other abnormalwater usage and communicating the leak to the local integration platform315 through the network 150. In one example, the local system 120 mayinclude external sensors 370 which are associated with a third-partyservice or entity. These sensors 370 may include moisture sensors, flowsensors, pressure sensors, etc. which are located remote from the watermonitoring device 310 and which are configured to send signals to thewater monitoring device 310 in order to identify leak conditions. Theselocal integration platform 315 may include one or more components whichfacilitate a connection with the external sensors 370, such as Wi-Fi orBluetooth™ connections. In some embodiments, the third-party devices(e.g., external sensors 370) may collect data independently and transmitthe data to the third-party system 140. The third-party system 140 mayprovide the data to the back-end system 110 which in turn communicateswith the local system 120.

In step 920, the water monitoring device 310 categorizes the problem.For example, water monitoring device 310 may determine whether thedetected abnormal water usage represents a small leak or a major leak,as these situations may be handled differently. In step 930, the watermonitoring device 310 determines a protocol for alerting the user Pbased on the categorized leak. For example, if the leak is a small leak,a text message or similar alert may be delivered to the client device130. For larger leaks, such as a burst pipe or unattended runningfaucet, a third-party system 140 may be involved to provide a morecomprehensive alert and/or remedy to the situation.

In step 940, a message is pushed through the third-party system 140. Forexample, the water monitoring device 310 may determine that a major leakis occurring and perform a process through the local integrationplatform 315 that provides a message to a user P through a third-partysystem 140 or associated service. In one example, the local integrationplatform 315 may include connections (e.g., through the back-end system110) to a third-party security system. The local integration platform315 may cause a message to be sent to the third-party system 140associated with the security system, thereby notifying an entitymonitoring the status of the building 160. In another example, thethird-party system 140 may be associated with a home automation system.The local integration platform may cause a message to be sent throughthe home automation system such that the user P may receive water usagealerts in a centralized location with other home automation alerts.

It should be understood that the third-party integration messaging isnot limited to any particular leaks (e.g., major leaks) and can be usedto integrate the water monitoring device 310 and the associated messagesinto any third-party system. For example, the local integration platform315 may push a message through a third-party system to alert a userusing a client device 130 such as a smart speaker. The smart speaker mayproduce an audible message which alerts the user P of the small leak andthe location, if known.

The present disclosure includes one or more systems which provide awater monitoring device for monitoring water usage within a building.The water monitoring system includes one or more components which areconfigured to collect data from multiple sources, including differentwater monitoring devices as well as third-party devices, in order toperform machine learning processes in order to generate rules or controllogic which accurately represent water flow as either intended orunintended. The integration of third-party devices through anintegration platform enables the overall water monitoring system tocollect additional data which is useful in assessing water flow, as wellas providing additional routes for alerting and/or otherwisecommunicating with a user (e.g., through a client device). The overallsystem fits into an overall home automation scheme and provides anadditional resource to the user, monitoring the water usage, providingfeedback, and taking corrective actions where necessary to avoidunnecessary damage and expense due to unintended water usage.

FIGS. 10-13 are exemplary user interfaces 1000, 1100, 1200, and 1300which may be implemented through the back-end system 110 and displayedto a user P through the client device 130. In one embodiment, interfaces1000 and 1100 include an exemplary web browser arrangement. Interfaces1200 and 1300 are suitable for the control panel 540 or a mobileapplication which is presented through the client device 130.

As shown in FIG. 10, the user interface 1000 includes a dashboardsection which provides some information about the status of the watermonitoring device 310 and the associated water flow. The information mayinclude, for example, the current water flow, past water flow, status ofthe automatic shut-off valve, status of whether a leak is detected,“home” or “away” mode status, and water temperature (current and pasttemperature). This information provides a snapshot of the status of thewater flow and provides feedback to the user which is not present in aconventional water meter. As shown in FIG. 11, the user interface 1100includes an input settings interface which enables a user P to provideinformation. For example, the user interface 1100 includes an option forthe user P to input customized thresholds for detecting a leak. The userinterface 1100 also includes input fields for connecting the watermonitoring device 310 to the network 150, such as a Wi-Fi network. Asshown in FIGS. 12-13, the user interfaces 1200 and 1300 include anotherrepresentation of the dashboard and include flow rate, current usage,leak detection, valve status, and “home” or “away” status.

The embodiments of the present disclosure may be implemented with anycombination of hardware and software. For example, computing platforms(e.g., servers, desktop computer, etc.) may be specially configured toperform the techniques discussed herein.

In addition, the embodiments of the present disclosure may be includedin an article of manufacture (e.g., one or more computer programproducts) having, for example, computer-readable, non-transitory media.The media may have embodied therein computer readable program code forproviding and facilitating the mechanisms of the embodiments of thepresent disclosure. The article of manufacture can be included as partof a computer system or sold separately.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims. The system andprocesses of the figures are not exclusive. Other systems, processes andinterfaces may be derived in accordance with the principles of theinvention to accomplish the same objectives. Although this invention hasbeen described with reference to particular embodiments, it is to beunderstood that the embodiments and variations shown and describedherein are for illustration purposes only. Modifications to the currentdesign may be implemented by those skilled in the art, without departingfrom the scope of the invention.

1. A computer-implemented method for detecting a leak in a water flowsystem, comprising: connecting to a water monitoring device and athird-party system; receiving water flow data from the water monitoringdevice, receiving location data from the third-party system; determininga threshold parameter based on the location data; and comparing thewater flow data to the threshold parameter in order to determine thatthere is a leak in the water flow system.
 2. The computer-implementedmethod of claim 1, further comprising authenticating the connection tothe water monitoring device and the third-party system to the same user.3. The computer-implemented method of claim 1, wherein the water flowdata includes water pressure.
 4. The computer-implemented method ofclaim 1, wherein the water flow data includes flow rate.
 5. Thecomputer-implemented method of claim 1, wherein determining a thresholdparameter based on the location data includes determining whether thewater monitoring device is in a home or away mode.
 6. Thecomputer-implemented method of claim 1, wherein the third-party systemis a security system and the location data includes an armed status ofthe security system.
 7. The computer-implemented method of claim 1,wherein the third-party system is a virtual assistant system and thelocation data is based on the detection of a voice within the range of athird-party device associated with the virtual assistant system.
 8. Thecomputer-implemented method of claim 1, further comprising sending analert instruction to a client device indicating that a leak wasdetected.
 9. The computer-implemented method of claim 8, wherein theclient device is a component of the third-party system and the alert isdirected to the client device through a back-end system device.
 10. Thecomputer-implemented method of claim 9, wherein the client device is asmart speaker and the alert is an audible alert played through the smartspeaker.
 11. A water monitoring system, comprising: a back-end systemcomprising an authentication module, a machine learning module, analerts module, and a third-party module, wherein the back-end system isconfigured to remotely connect to a local system comprising a watermonitoring device and the authentication module is configured toauthenticate the connection related to a user, the back-end system isconfigured to remotely connect to a third-party system using thethird-party module and the authentication module is configured toauthenticate the connection related to the same user, the back-endsystem receives data from the local system and the third-party system,the machine learning module is configured to analyze the data todetermine one or more rules which identify water usage as intended orunintended, and the alerts module is configured to provide an alert toone or more of the local system, the third-party system, or a clientdevice when the water monitoring device measures water flow data whichindicates a leak according to the one or more rules.
 12. The watermonitoring system of claim 11, wherein the data received from the localsystem includes water flow data.
 13. The water monitoring system ofclaim 12, wherein the water flow data includes water pressure data. 14.The water monitoring system of claim 12, wherein the water flow dataincludes flow rate data.
 15. The water monitoring system of claim 12,wherein the water flow data include vibration data.
 16. The watermonitoring system of claim 11, wherein the data received from thethird-party system is indicative of a location of a user.
 17. The watermonitoring system of claim 11, wherein the third-party module includesan open API module.
 18. The water monitoring system of claim 11, wherethe data received from the local system includes water usage statisticsand associated timing of the water usage.
 19. The water monitoringsystem of claim 18, wherein the machine learning module is configured toanalyze the data received from the local system and identify patterns ofintended water usage.